Transferability of motor skills from piano training to learning new laparoscopic surgical skills
Bibliographic record
Abstract
There is a widely held belief that musicians make better surgeons based on the far transfer of their established fine motor skills when learning new surgical skills. There is, however, a deficit of quantified knowledge on the transfer of fine motor skills from one domain of expertise to another. In this study, pianists and controls were provided with daily laparoscopic training sessions for five consecutive days. Each session consisted of six tasks on a Train Anywhere Skill Kit laparoscopic training box. Performance was evaluated each day and retention was evaluated one week later by measuring the speed and accuracy of task completion. Except for the bead to peg transfer task, no statistical differences were found between participant groups. The only significant confounding variable was that the control group was more interested in surgery than the musician group (p = .037). This research addressed limitations of previous studies by measuring the long-term performance and retention of laparoscopic surgical skills. The results of this study demonstrate that, contrary to expectations, piano performance training did not far transfer to laparoscopic surgery. Our findings indicate that fine motor skills are domain specific to music and surgery, respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".